# Load data
nsduh <- read.csv("../Data/Modified_2022_NSDUH.csv", stringsAsFactors = TRUE)

# Subset adults only
adults <- nsduh[!nsduh$is_minor, ] # subset for all (not) minor
rm(nsduh) # dump original df

# Remove never-drinkers
adults <- adults[!(adults$predictor.alcage_category == 0), ]

# Create dummy predictor variable
adults$drank_as_minor <- (adults$predictor.alcage_category == 3)

# Run dummy regressions
alcbinge.olsmod <- lm(response.lifetime_alcbinge ~ drank_as_minor, data = adults)
cocaine.olsmod <- lm(response.lifetime_cocaine ~ drank_as_minor, data = adults)
ecstacy.olsmod <- lm(response.lifetime_ecstacy ~ drank_as_minor, data = adults)
heroin.olsmod <- lm(response.lifetime_heroin ~ drank_as_minor, data = adults)
meth.olsmod <- lm(response.lifetime_meth ~ drank_as_minor, data = adults)
sud.olsmod <- lm(response.lifetime_sud ~ drank_as_minor, data = adults)

# Export models
save(alcbinge.olsmod,
     cocaine.olsmod,
     ecstacy.olsmod,
     heroin.olsmod,
     meth.olsmod,
     sud.olsmod,
     file = "../Results/Analysis_1.rdata")